Home Location Estimation Using Weather Observation Data

We can extract useful information from social media data by adding the user's home location. However, since the user's home location is generally not publicly available, many researchers have been attempting to develop a more accurate home location estimation. In this study, we propose a method to estimate a Twitter user's home location by using weather observation data from AMeDAS. In our method, we first estimate the weather of the area posted by an estimation target user by using the tweet, Next, we check out the estimated weather against weather observation data, and narrow down the area posted by the user. Finally, the user's home location is estimated as which areas the user frequently posts from. In our experiments, the results indicate that our method functions effectively and also demonstrate that accuracy improves under certain conditions.Comment: The 2017 International Conference On Advanced Informatics: Concepts, Theory And Application (ICAICTA2017

Analysis of Home Location Estimation with Iteration on Twitter Following Relationship

User's home locations are used by numerous social media applications, such as social media analysis. However, since the user's home location is not generally open to the public, many researchers have been attempting to develop a more accurate home location estimation. A social network that expresses relationships between users is used to estimate the users' home locations. The network-based home location estimation method with iteration, which propagates the estimated locations, is used to estimate more users' home locations. In this study, we analyze the function of network-based home location estimation with iteration while using the social network based on following relationships on Twitter. The results indicate that the function that selects the most frequent location among the friends' location has the best accuracy. Our analysis also shows that the 88% of users, who are in the social network based on following relationships, has at least one correct home location within one-hop (friends and friends of friends). According to this characteristic of the social network, we indicate that twice is sufficient for iteration.Comment: The 2016 International Conference on Advanced Informatics: Concepts, Theory and Application (ICAICTA2016

Work and Home Location: Possible Role of Social Networks

This research explores to what extent people's work locations are similar to that of those who live around them. Using the Longitudinal Economic and Household Dynamics data set and the US census for the Twin Cities (Minneapolis-St. Paul) metropolitan area, we investigate the home and work locations of different census block residents. Our aim is to investigate if people who live close to one another, also work close to one another to a degree beyond what would be expected at random. We find a significantly non-random correlation between joint home and joint work locations. Further, we show what features of particular neighborhoods are associated with comparatively higher incidences of people sharing work locations. One reason for such an outcome can be the role neighborhood level social networks play in locating jobs; or conversely work place social networks play in choosing the home location or both. Such findings should be used to refine work trip distribution models that otherwise depend mainly on impedance between the origin and destination.Social Networks, Trip Distribution, Destination Choice, Work, Commuting, Residential Location

Remittances as investment in the absence of altruism

In the absence of altruism, there is no obvious reason why a migrant should remit part of his income to his family for investment at the home location. If the family invests such income (in housing for example), why would they give it back to the migrant when he returns? This paper is based on the idea that certain people at a migrant's home location may punish those families who do not return those investments in order to prevent their own possibilities of receiving future remittances and investments from being adversely affected. We find that in equilibrium we can have remittances to be invested and given back to the migrant and remittances for private consumption by the migrant's family even in the complete absence of altruism on either the part of the migrant or his family. --Remittances,Altruism,Migration

Determination of User Home Location for Emergency Services

This disclosure describes techniques to accurately determine a user’s home location for use in voice over WiFi (VoWiFi) emergency calls. Per techniques of this disclosure, with user permission, a user’s home location is determined on a user device based on location information and corresponding time signatures associated with the locations. Based on user location data, location clusters and sub-clusters are created. Based on the identified sub-clusters, a home cluster is identified and labeled as the user home location based on the location sub-cluster with time signatures representing the end of day and/or the location sub-cluster where the user has spent the longest stationary time. If the determined home location address is different from the current emergency address associated with the user, the user is prompted to update their emergency address to the newly determined home location address. The process is performed entirely on the user device

Technical report on Optimization-Based Bearing-Only Visual Homing with Applications to a 2-D Unicycle Model

We consider the problem of bearing-based visual homing: Given a mobile robot which can measure bearing directions with respect to known landmarks, the goal is to guide the robot toward a desired "home" location. We propose a control law based on the gradient field of a Lyapunov function, and give sufficient conditions for global convergence. We show that the well-known Average Landmark Vector method (for which no convergence proof was known) can be obtained as a particular case of our framework. We then derive a sliding mode control law for a unicycle model which follows this gradient field. Both controllers do not depend on range information. Finally, we also show how our framework can be used to characterize the sensitivity of a home location with respect to noise in the specified bearings. This is an extended version of the conference paper [1].Comment: This is an extender version of R. Tron and K. Daniilidis, "An optimization approach to bearing-only visual homing with applications to a 2-D unicycle model," in IEEE International Conference on Robotics and Automation, 2014, containing additional proof

The assessment of traffic livability, including local effects at home, during trips and at the destination, based on the individual activity pattern and trip behaviour

The environmental quality of the living environment is mainly linked to the direct and indirect impact of traffic in the neighborhood of the dwellings. In the Flemish mobility and urban planning, the term ‘livability’ is used focusing on the living conditions of people’s home location: what is the satisfaction about their living environment? The more specific term ‘traffic livability’ is used to describe the impact of all types of traffic on the livability of a dwelling location. Some methodologies were developed for an objective measurement of the traffic impact on quality of life. In Flanders the most commonly used methodologies are the ‘traffic livability index’ and the ‘bearing capacity’, which use a very narrow interpretation of the traffic livability, as they are highly based on the local road design (number of lanes, cycle path, …) and the local traffic characteristics (traffic flow, speed, traffic safety, …) of the street of the dwelling. The main critic is that these methods should measure over the complete living environment of a person, rather than just at the dwelling. For this reason, an alternative methodology was developed for an objective measurement of the impact of traffic on the local quality of the living environment. Compared to the current practice, this new methodology aims at the following objectives: • The evaluation is not done for the average person, but includes individual needs and travel patterns, based on personal characteristics, representing the large diversity of the mobility needs. • The methodology should reflect a daily activity pattern, including the traveled routes and destinations. The traffic livability of a specific household in a specific area will reflect the full extent of their needs at home, during the trips and at the destinations. • Traffic livability is measured by means of a broad set of indicators, representing different types of traffic impacts (accessibility, traffic noise, traffic emissions, …). The separate indicators are combined into an evaluation of the traffic livability, including an extensive set of secondary effects. This is mainly realized by a better simulation of the personal trip behavior, using the data from the Flemish Trip Behavior Survey. In order to evaluate the livability at a certain home location (a number of) households are sampled from this database, with the specific characteristics of the household (composition, car availability, children, …), the people in the household (age, employment, …) and their activities and trip pattern. With this information, the different indicators for traffic livability can be evaluated on the home location, as well as during the trip and at the destination